Visualization of the Current Trending Searches

Team: 11

School: Everest Academy

Area of Science: Data Visualization

The purpose of this project is to dynamically visualize popular internet searches via Google Trends[1], by compiling them into a data visualization illustrated by the image results from those terms. By "dynamic," I am referring to the visualization updating in real-time as trending searches change.

I will be developing this in Python. Unfortunately, Google Trends does not offer an API for Python (or any other language), but General Mills has published an unofficial Python API[2]. Dynamically visualizing data is not a new idea[3], but doing so in a fully automated way remains an eternally underused and underrated angle.

I have researched into other trend platforms, but none have Google's market share dominance and so would provide limited insight into more frequently searched terms. I looked into a couple other library options, and found one obvious choice for Python for tapping into Google Trends. I am currently taking a crash course[4] on Python.

I expect to produce a demo showcasing the basic functionality (dynamic/real-time visualization of Google Trends data). The lack of official API support means that, for example, the prototype may not be scalable or distributable, as well as not having much/any additional functionality (such as that found in Polymath Technologies' Optima[5]) that would be useful for an end user such as hedge fund managers.


Team Members: Emily Edington

Mentor: Creighton Edington

Team Members:

  Emily Edington

Sponsoring Teacher: Creighton Edington

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